1. Econometric analysis [2012]
- Book
- xxxix, 1,198 p. : ill. ; 24 cm.
- Part I: The Linear Regression Model Chapter 1: Econometrics Chapter 2: The Linear Regression Model Chapter 3: Least Squares Chapter 4: The Least Squares Estimator Chapter 5: Hypothesis Tests and Model Selection Chapter 6: Functional Form and Structural Change Chapter 7: Nonlinear, Semiparametric, and Nonparametric Regression Models Chapter 8: Endogeneity and Instrumental Variable Estimation Part II: Generalized Regression Model and Equation Systems Chapter 9: The Generalized Regression Model and Heteroscedasticity Chapter 10: Systems of Equations Chapter 11: Models for Panel Data Part III: Estimation Methodology Chapter 12: Estimation Frameworks in Econometrics Chapter 13: Minimum Distance Estimation and the Generalized Method of Moments Chapter 14: Maximum Likelihood Estimation Chapter 15: Simulation-Based Estimation and Inference Chapter 16: Bayesian Estimation and Inference Part IV: Cross Sections, Panel Data, and Microeconometrics Chapter 17: Discrete Choice Chapter 18: Discrete Choices and Event Counts Chapter 19: Limited Dependent Variables--Truncation, Censoring, and Sample Selection Part V: Time Series and Macroeconometrics Chapter 20: Serial Correlation Chapter 21: Models with Lagged Variables Chapter 22: Time-Series Models Chapter 23: Nonstationary Data Part VI: Appendices Appendix A: Matrix Algebra Appendix B: Probability and Distribution Theory Appendix C: Estimation and Inference Appendix D: Large-Sample Distribution Theory Appendix E: Computation and Optimization Appendix F: Data Sets Used in Applications Appendix G: Statistical Tables.
- (source: Nielsen Book Data)9780131395381 20160606
(source: Nielsen Book Data)9780131395381 20160606
- Part I: The Linear Regression Model Chapter 1: Econometrics Chapter 2: The Linear Regression Model Chapter 3: Least Squares Chapter 4: The Least Squares Estimator Chapter 5: Hypothesis Tests and Model Selection Chapter 6: Functional Form and Structural Change Chapter 7: Nonlinear, Semiparametric, and Nonparametric Regression Models Chapter 8: Endogeneity and Instrumental Variable Estimation Part II: Generalized Regression Model and Equation Systems Chapter 9: The Generalized Regression Model and Heteroscedasticity Chapter 10: Systems of Equations Chapter 11: Models for Panel Data Part III: Estimation Methodology Chapter 12: Estimation Frameworks in Econometrics Chapter 13: Minimum Distance Estimation and the Generalized Method of Moments Chapter 14: Maximum Likelihood Estimation Chapter 15: Simulation-Based Estimation and Inference Chapter 16: Bayesian Estimation and Inference Part IV: Cross Sections, Panel Data, and Microeconometrics Chapter 17: Discrete Choice Chapter 18: Discrete Choices and Event Counts Chapter 19: Limited Dependent Variables--Truncation, Censoring, and Sample Selection Part V: Time Series and Macroeconometrics Chapter 20: Serial Correlation Chapter 21: Models with Lagged Variables Chapter 22: Time-Series Models Chapter 23: Nonstationary Data Part VI: Appendices Appendix A: Matrix Algebra Appendix B: Probability and Distribution Theory Appendix C: Estimation and Inference Appendix D: Large-Sample Distribution Theory Appendix E: Computation and Optimization Appendix F: Data Sets Used in Applications Appendix G: Statistical Tables.
- (source: Nielsen Book Data)9780131395381 20160606
(source: Nielsen Book Data)9780131395381 20160606
Business Library
Business Library | Status |
---|---|
On reserve at Business Library | |
HB139 .G74 2012 | Unknown 2-hour loan |
MGTECON-604-01
- Course
- MGTECON-604-01 -- Econometric Methods II
- Instructor(s)
- Yurukoglu, Ali
- Book
- xiii, 373 p. : ill ; 22 cm.
- List of Figures vii List of Tables ix Preface xi Acknowledgments xv Organization of This Book xvii PART I: PRELIMINARIES 1 Chapter 1: Questions about Questions 3 Chapter 2: The Experimental Ideal 11 2.1 The Selection Problem 12 2.2 Random Assignment Solves the Selection Problem 15 2.3 Regression Analysis of Experiments 22 PART II: THE CORE 25 Chapter 3: Making Regression Make Sense 27 3.1 Regression Fundamentals 28 3.2 Regression and Causality 51 3.3 Heterogeneity and Nonlinearity 68 3.4 Regression Details 91 3.5 Appendix: Derivation of the Average Derivative Weighting Function 110 Chapter 4: Instrumental Variables in Action: Sometimes You Get What You Need 113 4.1 IV and Causality 115 4.2 Asymptotic 2SLS Inference 138 4.3 Two-Sample IV and Split-Sample IV 147 4.4 IV with Heterogeneous Potential Outcomes 150 4.5 Generalizing LATE 173 4.6 IV Details 188 4.7 Appendix 216 Chapter 5: Parallel Worlds: Fixed Effects, Differences-in-Differences, and Panel Data 221 5.1 Individual Fixed Effects 221 5.2 Differences-in-Differences 227 5.3 Fixed Effects versus Lagged Dependent Variables 243 5.4 Appendix: More on Fixed Effects and Lagged Dependent Variables 246 PART III: EXTENSIONS 249 Chapter 6: Getting a Little Jumpy: Regression Discontinuity Designs 251 6.1 Sharp RD 251 6.2 Fuzzy RD Is IV 259 Chapter 7: Quantile Regression 269 7.1 The Quantile Regression Model 270 7.2 IV Estimation of Quantile Treatment Effects 283 Chapter 8: Nonstandard Standard Error Issues 293 8.1 The Bias of Robust Standard Error Estimates 294 8.2 Clustering and Serial Correlation in Panels 308 8.3 Appendix: Derivation of the Simple Moulton Factor 323 Last Words 327 Acronyms and Abbreviations 329 Empirical Studies Index 335 References 339 Index 361.
- (source: Nielsen Book Data)9780691120348 20160528
(source: Nielsen Book Data)9780691120348 20160528
- List of Figures vii List of Tables ix Preface xi Acknowledgments xv Organization of This Book xvii PART I: PRELIMINARIES 1 Chapter 1: Questions about Questions 3 Chapter 2: The Experimental Ideal 11 2.1 The Selection Problem 12 2.2 Random Assignment Solves the Selection Problem 15 2.3 Regression Analysis of Experiments 22 PART II: THE CORE 25 Chapter 3: Making Regression Make Sense 27 3.1 Regression Fundamentals 28 3.2 Regression and Causality 51 3.3 Heterogeneity and Nonlinearity 68 3.4 Regression Details 91 3.5 Appendix: Derivation of the Average Derivative Weighting Function 110 Chapter 4: Instrumental Variables in Action: Sometimes You Get What You Need 113 4.1 IV and Causality 115 4.2 Asymptotic 2SLS Inference 138 4.3 Two-Sample IV and Split-Sample IV 147 4.4 IV with Heterogeneous Potential Outcomes 150 4.5 Generalizing LATE 173 4.6 IV Details 188 4.7 Appendix 216 Chapter 5: Parallel Worlds: Fixed Effects, Differences-in-Differences, and Panel Data 221 5.1 Individual Fixed Effects 221 5.2 Differences-in-Differences 227 5.3 Fixed Effects versus Lagged Dependent Variables 243 5.4 Appendix: More on Fixed Effects and Lagged Dependent Variables 246 PART III: EXTENSIONS 249 Chapter 6: Getting a Little Jumpy: Regression Discontinuity Designs 251 6.1 Sharp RD 251 6.2 Fuzzy RD Is IV 259 Chapter 7: Quantile Regression 269 7.1 The Quantile Regression Model 270 7.2 IV Estimation of Quantile Treatment Effects 283 Chapter 8: Nonstandard Standard Error Issues 293 8.1 The Bias of Robust Standard Error Estimates 294 8.2 Clustering and Serial Correlation in Panels 308 8.3 Appendix: Derivation of the Simple Moulton Factor 323 Last Words 327 Acronyms and Abbreviations 329 Empirical Studies Index 335 References 339 Index 361.
- (source: Nielsen Book Data)9780691120348 20160528
(source: Nielsen Book Data)9780691120348 20160528
Business Library
Business Library | Status |
---|---|
On reserve at Business Library | |
HB139 .A54 2009 | Unknown 2-hour loan |
HB139 .A54 2009 | Unknown 2-hour loan |
HB139 .A54 2009 | Unknown 2-hour loan |
MGTECON-604-01, FINANCE-633-01
- Course
- MGTECON-604-01 -- Econometric Methods II
- Instructor(s)
- Yurukoglu, Ali
- Course
- FINANCE-633-01 -- Advanced Empirical Corporate Finance
- Instructor(s)
- Seru, Amit
- Book
- x, 172 pages : illustrations ; 24 cm
- Introduction: Identification-- Tolerating Ambiguity. Part 1 Extrapolation: Predicting Criminality-- Probabilistic Prediction-- Inferring Conditional Distributions from Random-Sample Data-- Prior Distributional Information-- Predicting High School Graduation. Part 2 The Selection Problem: The Nature of the Problem-- Identification from Censored Samples Alone-- Bounding the Probability of Exiting Homelessness-- Prior Distributional Information-- Identification of Treatment Effects-- Information Linking Outcomes across Treatments-- Predicting High School Graduation If All Families Were Intact. Part 3 The Mixing Problem in Program Evaluation: The Experimental Evaluation of Social Programs-- Variation in Treatment-- The Perry Preschool Project-- Identification of Mixtures Using Only Knowledge of the Marginals-- Restrictions on the Outcome Distribution-- Restrictions on the Treatment Policy-- Identifying Combinations of Assumptions. Part 4 Response-Based Sampling: The odds Ratio and Public Health-- Bounds on Relative and Attributable Risk-- Information on Marginal Distributions-- Sampling from One Response Stratum-- General Binary Stratifications. Part 5 Predicting Individual Behaviour: Revealed Preference Analysis-- How Do Youth Infer the Returns to Schooling?-- Analysis of Intentions Data. Part 6 Simultaneity: "The" Identification Problem in Econometrics-- The Linear Market Model-- Equilibrium in Games-- Simultaneity with Downward-Sloping Demand. Part 7 The Reflection Problem: Endogenous, Contextual, and Correlated Effects-- A Linear Model-- A Pure Endogenous Effects Model-- Inferring the Composition of Reference Groups-- Dynamic Analysis.
- (source: Nielsen Book Data)9780674442832 20161213
- Preface Introduction Identification Tolerating Ambiguity 1 Extrapolation 1.1.
- (source: Nielsen Book Data)9780674442849 20161213
(source: Nielsen Book Data)9780674442832 20161213
- Introduction: Identification-- Tolerating Ambiguity. Part 1 Extrapolation: Predicting Criminality-- Probabilistic Prediction-- Inferring Conditional Distributions from Random-Sample Data-- Prior Distributional Information-- Predicting High School Graduation. Part 2 The Selection Problem: The Nature of the Problem-- Identification from Censored Samples Alone-- Bounding the Probability of Exiting Homelessness-- Prior Distributional Information-- Identification of Treatment Effects-- Information Linking Outcomes across Treatments-- Predicting High School Graduation If All Families Were Intact. Part 3 The Mixing Problem in Program Evaluation: The Experimental Evaluation of Social Programs-- Variation in Treatment-- The Perry Preschool Project-- Identification of Mixtures Using Only Knowledge of the Marginals-- Restrictions on the Outcome Distribution-- Restrictions on the Treatment Policy-- Identifying Combinations of Assumptions. Part 4 Response-Based Sampling: The odds Ratio and Public Health-- Bounds on Relative and Attributable Risk-- Information on Marginal Distributions-- Sampling from One Response Stratum-- General Binary Stratifications. Part 5 Predicting Individual Behaviour: Revealed Preference Analysis-- How Do Youth Infer the Returns to Schooling?-- Analysis of Intentions Data. Part 6 Simultaneity: "The" Identification Problem in Econometrics-- The Linear Market Model-- Equilibrium in Games-- Simultaneity with Downward-Sloping Demand. Part 7 The Reflection Problem: Endogenous, Contextual, and Correlated Effects-- A Linear Model-- A Pure Endogenous Effects Model-- Inferring the Composition of Reference Groups-- Dynamic Analysis.
- (source: Nielsen Book Data)9780674442832 20161213
- Preface Introduction Identification Tolerating Ambiguity 1 Extrapolation 1.1.
- (source: Nielsen Book Data)9780674442849 20161213
(source: Nielsen Book Data)9780674442832 20161213
Business Library
Business Library | Status |
---|---|
On reserve at Business Library | |
HA29 .M2465 1995 | Unknown 2-hour loan |
MGTECON-604-01
- Course
- MGTECON-604-01 -- Econometric Methods II
- Instructor(s)
- Yurukoglu, Ali